Sparrho

Sparrho

Sparrho combines human and artificial intelligence to help research professionals and layman users stay up-to-date with new scientific publications and patents.[2] Sparrho's recommendation engine provides personalized scientific news-feeds by using proprietary machine learning algorithms to "aggregate, distill and recommend" relevant content.[3] The platform aims to complement traditional methods of finding relevant academic material such as Google Scholar, and PubMed with a system which enables the serendipitous discovery of content and across relevant scientific fields.[4]

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Recommendation engine

Sparrho uses a "three-pronged approach" to content recommendation. Firstly, "data-data analysis" is tackled using techniques such as natural language processing to provide appropriate research based on data provided by users.[5] Secondly, "user-user interactions" are utilized to propose a wider range of potentially relevant subject areas to users with similar interests.[6] Finally, "user-data interactions" such as labeling articles as "relevant" or "irrelevant" within a particular scientific field allows Sparrho to personalize user newsfeeds.[7]

History

Sparrho was founded in 2013 by Vivian Chan and Nilu Satharasinghe as a solution to issues Chan encountered over the course of her biochemistry PhD at the University of Cambridge, especially in staying up to date with scientific literature [8][9][10] Initially established at Ideaspace in West Cambridge, and moving subsequently to Camden Collective[11] and the Ministry of Startups[12] in London, the company is now based in the data science hub SHACK15 in Shoreditch, London.[13]

In 2014, Chan was a semi-finalist for the 2014 Duke of York New Entrepreneur of the Year Award,[14][15] and in 2015, Chan was included on the 35 Women Under 35 list compiled by Management Today.[16] In 2016, Sparrho was a semi-finalist in Pitch@Palace 5.0.[17]

As of July 2017, Sparrho has raised $3 million from investors including White Cloud Capital, AllBright, and Beast Ventures.[18]

Competitors

Sparrho's primary competitors are PubChase and Scizzle,[10][19] though both PubChase and Scizzle are targeted towards biomedical sciences and solely recommend academic journal papers.[20][21]

See also


References

  1. "Sparrho's technology stack". StackShare.
  2. Glenski, Maria; Weninger, Tim (31 July 2017). "Predicting User-Interactions on Reddit". Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017. ASONAM '17. New York, NY, USA: Association for Computing Machinery. pp. 609–612. arXiv:1707.00195. doi:10.1145/3110025.3120993. ISBN 978-1-4503-4993-2. S2CID 649910.
  3. Nicola Davis (December 2013). "Cambridge's leading tech startups". The Guardian.
  4. Gibney, Elizabeth (2014). "How to tame the flood of literature". Nature News & Comment. 513 (7516): 129–130. doi:10.1038/513129a. PMID 25186906.
  5. "Tech Pitch: Sparrho". Startups.co.uk.

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